Telecom Churn Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Introduction**\n",
    "\n",
    "Churn rate is the percentage of subscribers to a service that discontinue their subscription to that service in a given time period.\n",
    "\n",
    "Customers are moving to other competitor companies due to below reasons.\n",
    "\n",
    "   - Poor service.\n",
    "   - Availability of features and content.\n",
    "   - Lower cost substitutes from competitors/ better offer from competitor.\n",
    "   - Negative customer service experiences\n",
    "   - Some unkown reasons\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Problem Statement**\n",
    "\n",
    "   - Reduce customer churn rate\n",
    "   - Analysis high risk customer group(customer group whose churn rate is more comapred to other clusters/customers)\n",
    "   - Predict whether the given customer will churn or not\n",
    "   \n",
    "### **Stakeholders**\n",
    "   - CEO\n",
    "   - Product Marketing Heads/Managers\n",
    "  \n",
    "### **Pain Point**\n",
    "   - To reduce loss of customer & increase revenue"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Business Metric\n",
    "   - To reduce churn rate by 5%\n",
    "   - To increase customer base\n",
    "   \n",
    "### Data Science Metric\n",
    "FN :Predicted customer will leave but in actual he will not <br>\n",
    "FP : Predicted will not leave but in actual he have left"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import the modules\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.metrics import classification_report, accuracy_score, confusion_matrix\n",
    "from sklearn.preprocessing import LabelEncoder, StandardScaler\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import AdaBoostClassifier\n",
    "from xgboost import XGBClassifier\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load the dataset\n",
    "\n",
    "- Load the train data and using all your knowledge try to explore the different statistical properties of the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>...</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1370</td>\n",
       "      <td>7596-IIWYC</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>27</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>20.25</td>\n",
       "      <td>538.2</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5676</td>\n",
       "      <td>9103-CXVOK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>19.75</td>\n",
       "      <td>19.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5800</td>\n",
       "      <td>7129-CAKJW</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>17</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>80.05</td>\n",
       "      <td>1345.65</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1645</td>\n",
       "      <td>9490-DFPMD</td>\n",
       "      <td>Female</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>42</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>84.65</td>\n",
       "      <td>3541.35</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>366</td>\n",
       "      <td>9069-LGEUL</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>23</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>59.95</td>\n",
       "      <td>1406</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5629</th>\n",
       "      <td>335</td>\n",
       "      <td>4322-RCYMT</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>68</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>75.80</td>\n",
       "      <td>5293.95</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5630</th>\n",
       "      <td>4714</td>\n",
       "      <td>0016-QLJIS</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>65</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>90.45</td>\n",
       "      <td>5957.9</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5631</th>\n",
       "      <td>2004</td>\n",
       "      <td>8565-CLBZW</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>24</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>89.85</td>\n",
       "      <td>2165.05</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5632</th>\n",
       "      <td>227</td>\n",
       "      <td>2232-DMLXU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>55.20</td>\n",
       "      <td>55.2</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5633</th>\n",
       "      <td>2761</td>\n",
       "      <td>2408-WITXK</td>\n",
       "      <td>Female</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>10</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>34.70</td>\n",
       "      <td>329.8</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5634 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Id  customerID  gender  SeniorCitizen Partner Dependents  tenure  \\\n",
       "0     1370  7596-IIWYC  Female              0      No         No      27   \n",
       "1     5676  9103-CXVOK    Male              0     Yes        Yes       1   \n",
       "2     5800  7129-CAKJW  Female              0      No         No      17   \n",
       "3     1645  9490-DFPMD  Female              1      No         No      42   \n",
       "4      366  9069-LGEUL    Male              0     Yes         No      23   \n",
       "...    ...         ...     ...            ...     ...        ...     ...   \n",
       "5629   335  4322-RCYMT    Male              0     Yes        Yes      68   \n",
       "5630  4714  0016-QLJIS  Female              0     Yes        Yes      65   \n",
       "5631  2004  8565-CLBZW    Male              0      No         No      24   \n",
       "5632   227  2232-DMLXU  Female              0     Yes         No       1   \n",
       "5633  2761  2408-WITXK  Female              1      No         No      10   \n",
       "\n",
       "     PhoneService     MultipleLines InternetService  ...     DeviceProtection  \\\n",
       "0             Yes                No              No  ...  No internet service   \n",
       "1             Yes                No              No  ...  No internet service   \n",
       "2             Yes               Yes     Fiber optic  ...                  Yes   \n",
       "3             Yes               Yes     Fiber optic  ...                   No   \n",
       "4             Yes                No             DSL  ...                   No   \n",
       "...           ...               ...             ...  ...                  ...   \n",
       "5629          Yes               Yes             DSL  ...                  Yes   \n",
       "5630          Yes               Yes             DSL  ...                  Yes   \n",
       "5631          Yes               Yes     Fiber optic  ...                  Yes   \n",
       "5632          Yes                No             DSL  ...                   No   \n",
       "5633           No  No phone service             DSL  ...                   No   \n",
       "\n",
       "              TechSupport          StreamingTV      StreamingMovies  \\\n",
       "0     No internet service  No internet service  No internet service   \n",
       "1     No internet service  No internet service  No internet service   \n",
       "2                      No                   No                   No   \n",
       "3                      No                  Yes                   No   \n",
       "4                      No                   No                  Yes   \n",
       "...                   ...                  ...                  ...   \n",
       "5629                  Yes                   No                  Yes   \n",
       "5630                  Yes                  Yes                  Yes   \n",
       "5631                   No                  Yes                   No   \n",
       "5632                   No                  Yes                   No   \n",
       "5633                   No                   No                  Yes   \n",
       "\n",
       "            Contract PaperlessBilling              PaymentMethod  \\\n",
       "0           Two year              Yes  Bank transfer (automatic)   \n",
       "1     Month-to-month               No           Electronic check   \n",
       "2     Month-to-month               No  Bank transfer (automatic)   \n",
       "3     Month-to-month              Yes           Electronic check   \n",
       "4     Month-to-month              Yes  Bank transfer (automatic)   \n",
       "...              ...              ...                        ...   \n",
       "5629        One year              Yes  Bank transfer (automatic)   \n",
       "5630        Two year              Yes               Mailed check   \n",
       "5631  Month-to-month              Yes               Mailed check   \n",
       "5632  Month-to-month               No               Mailed check   \n",
       "5633  Month-to-month              Yes           Electronic check   \n",
       "\n",
       "     MonthlyCharges TotalCharges  Churn  \n",
       "0             20.25        538.2     No  \n",
       "1             19.75        19.75     No  \n",
       "2             80.05      1345.65     No  \n",
       "3             84.65      3541.35    Yes  \n",
       "4             59.95         1406     No  \n",
       "...             ...          ...    ...  \n",
       "5629          75.80      5293.95    Yes  \n",
       "5630          90.45       5957.9     No  \n",
       "5631          89.85      2165.05    Yes  \n",
       "5632          55.20         55.2    Yes  \n",
       "5633          34.70        329.8    Yes  \n",
       "\n",
       "[5634 rows x 22 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Code starts here\n",
    "train = pd.read_csv('data/train.csv')\n",
    "train\n",
    "# Code ends here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5634, 22)"
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     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "# Shape of data\n",
    "train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>tenure</th>\n",
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       "      <th>count</th>\n",
       "      <td>5634.000000</td>\n",
       "      <td>5634.000000</td>\n",
       "      <td>5634.000000</td>\n",
       "      <td>5634.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3520.088569</td>\n",
       "      <td>0.161519</td>\n",
       "      <td>32.075790</td>\n",
       "      <td>64.671166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2028.634870</td>\n",
       "      <td>0.368042</td>\n",
       "      <td>24.492631</td>\n",
       "      <td>30.177218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>18.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1767.250000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>35.275000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3512.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>70.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5282.750000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>90.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7042.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>118.750000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "                Id  SeniorCitizen       tenure  MonthlyCharges\n",
       "count  5634.000000    5634.000000  5634.000000     5634.000000\n",
       "mean   3520.088569       0.161519    32.075790       64.671166\n",
       "std    2028.634870       0.368042    24.492631       30.177218\n",
       "min       0.000000       0.000000     0.000000       18.250000\n",
       "25%    1767.250000       0.000000     9.000000       35.275000\n",
       "50%    3512.000000       0.000000    28.000000       70.350000\n",
       "75%    5282.750000       0.000000    55.000000       90.050000\n",
       "max    7042.000000       1.000000    72.000000      118.750000"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(train['TotalCharges'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Id                  0\n",
       "customerID          0\n",
       "gender              0\n",
       "SeniorCitizen       0\n",
       "Partner             0\n",
       "Dependents          0\n",
       "tenure              0\n",
       "PhoneService        0\n",
       "MultipleLines       0\n",
       "InternetService     0\n",
       "OnlineSecurity      0\n",
       "OnlineBackup        0\n",
       "DeviceProtection    0\n",
       "TechSupport         0\n",
       "StreamingTV         0\n",
       "StreamingMovies     0\n",
       "Contract            0\n",
       "PaperlessBilling    0\n",
       "PaymentMethod       0\n",
       "MonthlyCharges      0\n",
       "TotalCharges        0\n",
       "Churn               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Check missing values\n",
    "train.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No     4120\n",
       "Yes    1514\n",
       "Name: Churn, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Value counts of target coloumn\n",
    "train['Churn'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Visualize the data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Churn', ylabel='count'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Graphical count of customer churn\n",
    "sns.countplot(train['Churn'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "73.12744053958112 % of customers stayed in the company\n",
      "26.872559460418888 % of customers left the company\n"
     ]
    }
   ],
   "source": [
    "# To check the percentage of customers that are leaving\n",
    "\n",
    "num_retianed = train[train.Churn == 'No'].shape[0]\n",
    "num_churned = train[train.Churn == 'Yes'].shape[0]\n",
    "\n",
    "#Print the percentage of customers that stayed\n",
    "print(num_retianed/(num_retianed+num_churned)*100, '% of customers stayed in the company')\n",
    "#Print the percentage of customers that left\n",
    "print(num_churned/(num_retianed+num_churned)*100, '% of customers left the company')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Churn count for both males & females"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='gender',hue = 'Churn', data= train);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Insights:** No impact of churn rate with specific gender<br>\n",
    "**Recommendation:** Focus on both the genders."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Churn count for internet services"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='InternetService', ylabel='count'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='InternetService', hue='Churn', data = train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Insights:** Customer with Fiber optic service tends to have higher churn rate compared to others<br>\n",
    "**Recommendation:** Company needs to look for reason of higher churn rate into Fiber optic service provider department "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2016x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_features = ['tenure', 'MonthlyCharges']\n",
    "fig, ax = plt.subplots(1,2, figsize=(28,8))\n",
    "train[train.Churn == 'No'][num_features].hist(bins = 20, color='blue', alpha = 0.5, ax=ax)\n",
    "train[train.Churn == 'Yes'][num_features].hist(bins = 20, color='red', alpha = 0.5, ax=ax);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Insights**<br>\n",
    "**Tenure :** For low tenure churn rate is higher whereas with high tenure churn rate is pretty low<br>\n",
    "**Monthly Charges :** Customer churn rate is high when charges exceeds 70<br>\n",
    "\n",
    "**Recommendation**<br>\n",
    "**Tenure :** Try to include more long tenure plans<br>\n",
    "**Monthky Charges :** To keep existing customers & acquire new customer keep the monthly charges below 70"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create new subset with Monthly charges exceeding 70\n",
    "df_new = train[train['MonthlyCharges']>70]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='InternetService', ylabel='count'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='InternetService', hue='Churn', data = df_new)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Insights:** Fiber optic have charges more than 70<br>\n",
    "**Recommendation:** Kindly look for the competitor prices & services. Contact with existing & non-existing customers for feedback  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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pNUlPlZSdLelZSZMl3Sjpc7m8QdIHkibl24UlxwyV9KSkqZLGSFK5YjYzs5aVsxnqMmCnZmV3ARtGxGDgn8DJJdteiIgh+XZkSfkFwAhgnXxrfk4zMyuzsiWLiHgQeLNZ2f9GxPz88O9Am5OpS1oVWC4iHom02sgVwB5lCNfMzNpQzQ7uw4A7Sh4PlPSEpAckbZnLVgcaS/ZpzGVmZlZBVenglvQTYD5wdS6aCQyIiNmShgI3SRoEtNQ/0ep6hpJGkJqsGDBgQMcGbWZWxypes5B0MLAr8K3ctEREzIuI2fn+ROAFYF1STaK0qao/MKO1c0fE2IgYFhHD+vXrV65fwcys7lQ0WUjaCfgRsFtEvF9S3k9S93x/LVJH9osRMROYI+mreRTUQcDNlYzZzMzK2Awl6Rpga6CvpEbgNNLop17AXXkE7N/zyKf/As6QNB9YABwZEU2d40eRRlb1IfVxlPZzmJlZBZQtWUTE/i0UX9zKvtcD17eybQKwYQeGZmZmi8jTfZiZWSEnCzMzK+RkYWZmhZwszMyskJOFmZkVcrIwM7NCThZmZlbIycLMzAo5WZiZWSEnCzMzK+RkYWZmhZwszMyskJOFmZkVcrIwM7NCThZmZlbIycLMzAo5WZiZWSEnCzMzK1S2ZVXNzIoMPfGKaoewyCaefVC1Q6gK1yzMzKxQu5KFpM3bU9Zs+yWSXpP0VEnZCpLukvR8/rl8ybaTJU2V9JykHUvKh0p6Mm8bI0nt+9XMzKyjtLdmcV47y0pdBuzUrOwk4J6IWAe4Jz9G0gbAcGBQPuZ8Sd3zMRcAI4B18q35Oc3MrMza7LOQtCmwGdBP0nElm5YDurd8VBIRD0pqaFa8O7B1vn85cD/wo1x+bUTMA16SNBXYRNI0YLmIeCTHcwWwB3BHwe9lZmYdqKiDeylgmbzfsiXl7wB7L8bzrRwRMwEiYqaklXL56sDfS/ZrzGUf5vvNy83MrILaTBYR8QDwgKTLIuLlMsbRUj9EtFHe8kmkEaQmKwYMGNAxkZmZWbuHzvaSNBZoKD0mIrZdxOebJWnVXKtYFXgtlzcCa5Ts1x+Ykcv7t1DeoogYC4wFGDZsWKtJxczMFk17k8WfgQuBPwILluD5bgEOBs7KP28uKf+TpN8Aq5E6sh+LiAWS5kj6KvAocBDFHetmZtbB2pss5kfEBYtyYknXkDqz+0pqBE4jJYlxkg4HpgP7AETEFEnjgKeB+cDREdGUlI4ijazqQ+rYdue2mVmFtTdZ3Crpu8CNwLymwoh4s7UDImL/VjZt18r+o4HRLZRPADZsZ5xmZlYG7U0WB+efJ5aUBbBWx4ZjZmadUbuSRUQMLHcgZmbWebUrWUhqceasiKi9WcDMzGyRtbcZauOS+71J/Q6PA04WZmZ1oL3NUN8rfSzps8CVZYnIzMw6ncWdovx90rUQZmZWB9rbZ3ErH0+z0R1YHxhXrqDMzKxzaW+fxTkl9+cDL0dEY2s7m5lZ19KuZqg8oeCzpJlnlwf+U86gzMysc2nvSnn7Ao+RpufYF3hU0uJMUW5mZjWovc1QPwE2jojXACT1A+4G/lKuwMzMrPNo72iobk2JIpu9CMeamVmNa2/N4k5JfwWuyY/3A24vT0hmZtbZFK3B/XnSUqgnStoL2IK0et0jwNUViM/MzDqBoqak3wJzACLihog4LiJ+QKpV/La8oZmZWWdRlCwaImJy88K8xkRDWSIyM7NOpyhZ9G5jW5+ODMTMzDqvomQxXtIRzQvzsqgTyxOSmZl1NkWjoUYCN0r6Fh8nh2HAUsCeZYzLzMw6kTaTRUTMAjaTtA0fr4P9PxFxb9kjMzOzTqO961ncB9xX5ljMzKyTqvhV2JLWkzSp5PaOpJGSRkn6V0n5LiXHnCxpqqTnJO1Y6ZjNzOpde6/g7jAR8RwwBEBSd+BfwI3AocC5EVE6HTqSNgCGA4OA1YC7Ja0bEQsqGbeZWT2r9vxO2wEvRMTLbeyzO3BtRMyLiJeAqcAmFYnOzMyA6ieL4Xw83xTAMZImS7pE0vK5bHXglZJ9GnOZmZlVSNWShaSlgN2AP+eiC4C1SU1UM4FfN+3awuHRQhmSRkiaIGnC66+/3rEBm5nVsWrWLHYGHs/Dc4mIWRGxICI+Ai7i46amRmCNkuP6AzNaOmFEjI2IYRExrF+/fmUM3cysvlQzWexPSROUpFVLtu0JPJXv3wIMl9RL0kBgHdKqfWZmViEVHw0FIOkzwA7Ad0qKfyVpCKmJaVrTtoiYImkc8DQwHzjaI6HMzCqrKskiIt4HVmxWdmAb+48GRpc7LjMza1m1R0OZmVkNcLIwM7NCThZmZlbIycLMzAo5WZiZWSEnCzMzK+RkYWZmhZwszMyskJOFmZkVcrIwM7NCThZmZlbIycLMzAo5WZiZWSEnCzMzK+RkYWZmhZwszMyskJOFmZkVcrIwM7NCThZmZlbIycLMzApVJVlImibpSUmTJE3IZStIukvS8/nn8iX7nyxpqqTnJO1YjZjNzOpZNWsW20TEkIgYlh+fBNwTEesA9+THSNoAGA4MAnYCzpfUvRoBm5nVq87UDLU7cHm+fzmwR0n5tRExLyJeAqYCm1Q+PDOz+lWtZBHA/0qaKGlELls5ImYC5J8r5fLVgVdKjm3MZWZmViE9qvS8m0fEDEkrAXdJeraNfdVCWbS4Y0o8IwAGDBiw5FGamRlQpZpFRMzIP18DbiQ1K82StCpA/vla3r0RWKPk8P7AjFbOOzYihkXEsH79+pUrfDOzulPxZCFpaUnLNt0HvgY8BdwCHJx3Oxi4Od+/BRguqZekgcA6wGOVjdrMrL5VoxlqZeBGSU3P/6eIuFPSeGCcpMOB6cA+ABExRdI44GlgPnB0RCyoQtxmZnWr4skiIl4EvtRC+Wxgu1aOGQ2MLnNoZmbWis40dNbMzDopJwszMyvkZGFmZoWcLMzMrJCThZmZFXKyMDOzQk4WZmZWyMnCzMwKOVmYmVkhJwszMyvkZGFmZoWcLMzMrJCThZmZFXKyMDOzQk4WZmZWyMnCzMwKOVmYmVkhJwszMyvkZGFmZoWcLMzMrFDFk4WkNSTdJ+kZSVMkfT+Xj5L0L0mT8m2XkmNOljRV0nOSdqx0zGZm9a5HFZ5zPnB8RDwuaVlgoqS78rZzI+Kc0p0lbQAMBwYBqwF3S1o3IhZUNGozszpW8ZpFRMyMiMfz/TnAM8DqbRyyO3BtRMyLiJeAqcAm5Y/UzMyaVLXPQlIDsBHwaC46RtJkSZdIWj6XrQ68UnJYI20nFzMz62BVSxaSlgGuB0ZGxDvABcDawBBgJvDrpl1bODxaOecISRMkTXj99dc7PmgzszpVlWQhqScpUVwdETcARMSsiFgQER8BF/FxU1MjsEbJ4f2BGS2dNyLGRsSwiBjWr1+/8v0CZmZ1phqjoQRcDDwTEb8pKV+1ZLc9gafy/VuA4ZJ6SRoIrAM8Vql4zcysOqOhNgcOBJ6UNCmX/RjYX9IQUhPTNOA7ABExRdI44GnSSKqjPRLKzKyyKp4sIuIhWu6HuL2NY0YDo8sWlJmZtclXcJuZWSEnCzMzK+RkYWZmhZwszMyskJOFmZkVcrIwM7NCThZmZlbIycLMzAo5WZiZWaFqTPdhZlazpp/xxWqHsEgGnPpkh5zHNQszMyvkZGFmZoWcLMzMrJCThZmZFXKyMDOzQk4WZmZWyMnCzMwKOVmYmVkhJwszMyvkZGFmZoU83UeNqtcpB8ysOmqmZiFpJ0nPSZoq6aRqx2NmVk9qIllI6g78HtgZ2ADYX9IG1Y3KzKx+1ESyADYBpkbEixHxH+BaYPcqx2RmVjdqJVmsDrxS8rgxl5mZWQXUSge3WiiLT+0kjQBG5IfvSnqurFFV0ZrQF3ij2nG022ktvYX1qebeO/D7V6Lm3r9Ff+/WbKmwVpJFI7BGyeP+wIzmO0XEWGBspYKqJkkTImJYteOwRef3rrbV6/tXK81Q44F1JA2UtBQwHLilyjGZmdWNmqhZRMR8SccAfwW6A5dExJQqh2VmVjdqIlkARMTtwO3VjqMTqYvmti7K711tq8v3TxGf6ic2MzP7hFrpszAzsypysjAzs0JOFnVA0peqHYNVhiRfENHJSNpS0g7VjmNJOVl0cZI2Ay6WtF61Y7HykqTInZCSlpP0mWrHVO8kDQJOJ10rVtOcLLowSWsDPwROj4jnJNXM6DdbNHlizTXy/eOBG4ArJG1f1cDqWH5PfgBMjohnclnN1vycLLogZcB6pKkJDpTUK1+vUrN/rNay/J7+GDhd0teB7UhfEm4FLpS0UzXjq2Pvk6Yq+rykIQBRw8NPnSy6kJJEsCIsvDblROBN4DhJS0VESPL73kVI6pk/gA4CFgDHAn+LiMcj4nLgJ8AYSbtVM8560PT/J2mwpHXI/3ekSVC/KWnDasa3pPyh0YXkRPB10lQov5V0akQ8AlwDrAb8JCeMj6oaqHUIScsD6+eHmwKjgReBTSStkfswrgN+DpwhaekqhVoX8v/fN4DLgKOA3wFrAycDnwMOkVRbS1yWcLLoQiRtDfwCOII0K+b3JP0+Ih4AbgJW4ZMTMlptWw34tqSrgCuAacDRwNukGsWAnDCuALaMiPeqFmkdkDSY1By4MzATGAb8iNQcfBqwLDCvagEuISeLLiI3LX0GOICUEL4ObA9sJmlMRNwDnBwRL1QxTOsATc0deX60d4E9gPNy2UfA4UAv4EzSDM1ExJxqxFpnBHwX+CKwP3Ao6Uvb2cAg4OiI+Gf1wlsyThY1rKSNtAcs7KN4CTgYOC0i/gE8AOwqaYOIeLNqwVqHKB0em10CHAZsCBwsaZW8muQJwFvAh5WPsj6U/P+tKakP8M+IeIJUoxgVEROA54FngDkRMb960S45D6WsYbmNdDdgX6C3pD9GxJ2S3gZWlrQzsDLwtYiYWtVgbYk1u47iu8C6wBPA1aTEcAjwgaQvkGoWP8iJw8og///tTLqO4k5giKT9Sa/9b/KXuMOAwyNiUvUi7RiuWdQwSduQ2khPAf4D/DRvehDYFvgZMM6JomsoSRRbkZobZ5C+xf4G+BtwKbAxqflxnBNFeeXO6jNJ78V7QD9gQUScDlxJeh9OiYjx1Yuy43jW2Rom6VBSs9PypGaHb0fES3k45YeSPhcRb7XQdGE1StKBpOGYh0bEJElDgb2BPsDPI+INSctExLtVDbSLala7Wxf4GvAcaSTa8Ih4UdLGwASgW0Qs6Cr/f65Z1CBJQ/OKgUGqPXyX9If6kqQ9SVXgPqRRMTV9IVC9a+EiyoeABtLQTCJiIjCO1Ll6kqTuThTlk5ueNpV0AvAa6eLHi4GtcqLYilTbXzkiFjQdU72IO477LGrTKcBU0vjtI0gX/czKUzucSWqr/qCK8VkHaPYtdgjwYURMydNITJQ0KyJOjYgnJH0EzGj6gLKy+hD4Uq61n0Ca0mMfSXNIQ2RPi4hXqxphGThZ1IAWqrE/Iv2BBvAN4DrgD6Qhs8dHxJ2Vj9I6WkmiOBHYHfhI0hTSRZYbAX+X1CciTswj36wyXgf6Sdo8IsZJehM4BngZ+HFE3N5Vmp5Kuc+iRuTq7VzShVevATcCN0TEFSVNUp+NiDeqF6V1tDxtxBXAlqSLKjcltZOfAixDWmp4c2B2V/tw6kzy7LG/AEbm5qY9SddRHBIRbzarBXa5RAGuWdSSL5JGOH0A/A9pfP33Jd0ZEa8BSJpdxfisA7TwQbM0qfO6e0Q0SnoI2BPYISKukrRhRPhaivKbTmr6/XH+cvYQaTTa8qQ5oLqR5ubqMn0UzblmUUMkrUC6IvcsUj/FvsC2uc26S36bqSfNvp0OjIiX8v3zSB9I50TEHEk/Az6IiDMldfNcX5UjaQ3gC6SO7cHAvRGxf3WjqgwnixqQR7gsKHn8GdLU4z8F1gG2caLoOiR9j3SB3TTgXFLtYitgG1Lz43eAnSLi+SqFWHeahqOXPF6eNCrtBOBnEfFstWKrFA+d7WRKphBYXXm1szxWu0fT9oh4PyKmR8QRpBW4VqxmzLZkSofHSlqT1Nz4DeBJYD9gKWAMaRDD28AuThTlUfL/t6mknSRtCdC8qS8i/p2n9ugNrFn5SCvPfRadTB7HvRNpCOw/gLUl7RsRr7ZQw9gK+ArQvUrh2hJq1vR0EGmqiNcjYgYwStKPSJNCCrjSQ2PLq2QKnZ8C1wM7Sro00sy9C+WJO1cnjUB8qfKRVp5rFp2MpM8DvwJGki62ewB4WFLfFj4oGklNULMqG6V1lJJEsRepHXwVYC9JP8jbf0ma7noH0rdYKyNJy5KaALcn/X/1Bu6U9IkvZBHxUUS8QmoOrNmZZBeF+yw6gWbfLlcCfhURhzSVS7oAmBoRv65upFYOknYgzRR8YUQ8JOkrwO+BqyPi3LzPCuFZg8tO0udITX4vkpoDD4uIqZK+Bvwr0rTw1OPAAtcsOoGSKQR+Thr1spGkQ0o6rf+J36uubCCpOWOrPJ/Xo6Ra5dGSjgFwoiiPkj6KvpJ6RMRbwFOkmRFOyYliK9KqdwtrF/WWKMB9FlXVbLjrC6ROzXuAbwP3SupPaoI4mLSWtnVBETFW0n9Io522lXR3RDwmaT/Slwcrk/xFbVdSE+ACSSeRphtfCvi1pFuB4cCJETG5iqFWnZuhqiDP7bNhnipgZ9Kyi38Avkpqmx4FbADsQ/qjvcdTeHQ9+Vttj6aRNpK+CewK/C9wW3h1u7KT9GXSdUs/JC2H+mXgImA8sBmpNvF6RDxS79cyuWZRYZLWI83t85tcNIQ011M/0nj690jrJd8jaXJTdbfe/1BrXSvvnyJNJb8DcERE7Jtrk1sCt1U+yvoiaVXSQJK5kRYnmpSb/Y4gjUq7I0pWt6v3/z/XLCooJ4rbgMuA84GepPmefgVcS5rz5zDgfWD7iHixOpFaR2o2gOGbpDmd3ouIv+S5ny4CLoiI6/I+n8tt59aBJK1Fqj3MIc2l9T+SDgMOAq6IiEvyfj8gdW4f6rnWPuaaRYXkpqfLSVflfgD8EViL1B8xF/hmRHxP0nRSG2k/0ogMq3EliWIE8D1ScvhJrkXcDxwXEY/nDtb5ThQdL///3UKaV+0/wAGS/gBcRZpyfEtJCyLi8og4V9INThSf5JpFBSgtRHQ7KUHcRppe/N+kJqhX8+1Y0uiLayQtHxH/rlK4VgaSlgb+TFrrYHyuZZ4P/DkiLqxudF2bpM8CtwKXRsSluaw/aRnaB0mr3O1PqnXcGxGXuNn30zwcswIiLUS0f0RcHRFvk1Y2W560HON00lC9bsAIpSUxnShqnKQV87dZJG1K6o96HlhHaQ2K54DTgV0k9axiqPVgHmmtiXEAknpHRCOpyfdIYDfSnFt3AY+B+yda4mRRIZFXzsoX8zxN6uTuQ7pi903SSKhTwkti1rw8ymkV4DhJl5NWNJxL+sDamjTSjbzPh6S1SKx8+gBDSa89ETFX0lL5CuzzgHUj4n3gmoh4qnphdm5OFhXWNLopf7O8ijSdwIHAOxHxcDVjs46Rv5U+S5rP6RvAXyPinYj4DfAWKYncAhwPnF464sY6Xq6p/w74ptLytJDXniAl6j75vt+HNrjPosryaBjVy/wy9SRPSNcf2A64MSKuyuVDSJ2s7+TmECszSf1Iw2RXAP6Sh6ZvBlxNmtLjvmrGVwucLMzKKDdJ7QccAFxIao4aHBG/rWZc9UjSyqT34mjSRXfrA2dExM1VDaxGOFmYLaGSCR+bfnYDukXEfEmrkQYzfIE0Cm5FYM+og8VyOitJq+S7vSNimkc+tY+ThVkHkbRK00CG/Hg70lQSB0TE87kppEdEzKxakGaLyRflmS2mPK/Q0hHxf0pLoX5b0njSwIVnSUMyz86JontEvF7NeM2WhGsWZoshXxvx38C+pKuCNyNNAHkYaaTNPcCjETFbzVY4NKtFHjprthjyTLHXkq7K3x14Ik9h/VPSOtnbAZs5UVhX4WRhtgjyIjk75YebkC6ovIk019BWeVrxs0lDYzfDS6FaF+FmKLNFkOcZOp+0ut1cUq0igG+RLsA7OyIeyPOBLe3J6KyrcM3CbBHkub0eJC1Y9WJEzMlTtNxEmqzuZ5K2jIgPnCisK3GyMCvQtE5ziVuAHYH+ksYARMQs4O+kuYamVTRAswpwM5RZG5otXHQE8CXgHxFxkaS1ScvhTgYeAHYBTvByqNYVuWZh1oaSRLEvMAJ4GDhF0kkR8QJpEsi1gROAMU4U1lW5ZmFWIE84dwLwh4j4a1646Crghoj4Rd7ns7k/w6xLcs3CrJkW+ihWJS1etJuk1fL08gcAh0s6ERZ2fJt1Wa5ZmJVo1kcxGJhDWs3wK6S10Z8HxkXErNxn8VFEvFS1gM0qxMnCrAWSjgGOICWHNUjzPH0x/2wELouI16oXoVlluRnKDJC0fMn9YcDBwM4RsTdwP+k6ir8Bd5MW0Pmw8lGaVY+ThdU9SV8D7pK0Qy56FXgGeA8gIn4EvAh8JyJuAUbnpTrN6oaThVm6GntD4ERJewBvAKsBXy/Z5ynStB54eKzVI69nYQbXAGsBrwCHAP8GjgWulrQRINIssgdUK0CzanPNwuqSpMF5tBOkmWP/A2wAXACcCHyWVLOYBMwG9ouIZ6oQqlmn4NFQVnckrQi8ThrVdBzwMvAE8DvSvE/Lk2aRvTgibqpSmGadimsWVnciYjawPdAfGAzsBFwBvA/0i4hrgRuA4ZKWbeEiPbO645qF1S1J2wGXAF8G9ib1STQChwK9wJ3ZZk2cLKyuSdoF+CWwaUS8K2mgr8g2+zSPhrK6FhG351am8ZI2b0oUpdN+mJmThVlTwugJ3J2v3g4nCrNPcjOUWSZpmbxEqpk142RhZmaFPHTWzMwKOVmYmVkhJwszMyvkZGFmZoWcLMwKSFpF0rWSXpD0tKTbJa27GOcZKekzHRRTgyTPgmsV42Rh1oY8L9SNwP0RsXZEbAD8GFh5MU43EmgxWUjqvojnasBTplsFOVmYtW0b4MOIuLCpICImAQ9JOlvSU5KelLQfgKStJd0v6S+SnpV0tZJjSQsq3Sfpvrzvu5LOkPQosKmkUyWNz+cc2zSBoaTPS7pb0j8kPS5pbeAsYEtJkyT9oLIvidUjX8Ft1rYNgYktlO8FDAG+BPQlTRfyYN62ETAImAE8DGweEWMkHQdsExFv5P2WBp6KiFMBJD0dEWfk+1cCuwK3AlcDZ0XEjZJ6k77knQScEBG7dvQvbNYS1yzMFs8WwDURsSAiZgEPABvnbY9FRGNEfERaPKmhlXMsAK4vebyNpEclPQlsCwyStCywekTcCBARcyPi/Y7/dcza5mRh1rYpwNAWytta42Jeyf0FtF6DnxsRCwByjeF8YO+I+CJwEdC74HnMKsbJwqxt9wK9JB3RVCBpY9I63ftJ6i6pH/BfwGMF55oDLNvKtt755xuSliGtr0FEvAM0StojP3evPKKqrXOZdTgnC7M25Nln9wR2yENnpwCjgD8Bk4F/kBLKDyPi1YLTjQXuaOrgbvY8b5FqE08CNwHjSzYfCBwraTLwN2CV/Nzzc6e3O7it7DyRoJmZFXLNwszMCjlZmJlZIScLMzMr5GRhZmaFnCzMzKyQk4WZmRVysjAzs0JOFmZmVuj/ASmQtBCMl3H4AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Contract Churn Rate\n",
    "sns.countplot(train['Contract'],hue=train['Churn'])\n",
    "plt.xlabel('Contract')\n",
    "plt.ylabel('Count')\n",
    "plt.title('Contract Churn Data')\n",
    "plt.xticks(rotation=45);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Insight:** Month-to-month contract has high Churn Rate.<br>\n",
    "**Recommendation:** Provide customer with packages with quaterly & semi-annual contract."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature Engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Code Starts here\n",
    "train = train.drop('customerID', axis =1)\n",
    "# Code ends here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Replacing spaces with 'NaN' in train dataset\n",
    "train['TotalCharges'].replace(' ',np.NaN, inplace=True)\n",
    "\n",
    "#Converting the type of column from X_train to float\n",
    "train['TotalCharges'] = train['TotalCharges'].astype(float)\n",
    "\n",
    "#Filling missing values\n",
    "train['TotalCharges'].fillna(train['TotalCharges'].mean(),inplace=True)\n",
    "# test['TotalCharges'].fillna(train['TotalCharges'].mean(), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Convert all non-numeric columns to numeric \n",
    "for column in train.columns:\n",
    "    if train[column].dtype == np.number:\n",
    "        continue\n",
    "    train[column] = LabelEncoder().fit_transform(train[column])\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Id                    int64\n",
       "gender                int32\n",
       "SeniorCitizen         int64\n",
       "Partner               int32\n",
       "Dependents            int32\n",
       "tenure                int64\n",
       "PhoneService          int32\n",
       "MultipleLines         int32\n",
       "InternetService       int32\n",
       "OnlineSecurity        int32\n",
       "OnlineBackup          int32\n",
       "DeviceProtection      int32\n",
       "TechSupport           int32\n",
       "StreamingTV           int32\n",
       "StreamingMovies       int32\n",
       "Contract              int32\n",
       "PaperlessBilling      int32\n",
       "PaymentMethod         int32\n",
       "MonthlyCharges      float64\n",
       "TotalCharges        float64\n",
       "Churn                 int32\n",
       "dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To check dtypes\n",
    "train.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>...</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Id</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.009507</td>\n",
       "      <td>0.005225</td>\n",
       "      <td>-0.002615</td>\n",
       "      <td>0.001807</td>\n",
       "      <td>0.008353</td>\n",
       "      <td>-0.027008</td>\n",
       "      <td>-0.005665</td>\n",
       "      <td>-0.001766</td>\n",
       "      <td>0.007574</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.002294</td>\n",
       "      <td>0.002778</td>\n",
       "      <td>-0.005301</td>\n",
       "      <td>-0.022339</td>\n",
       "      <td>0.005255</td>\n",
       "      <td>0.000142</td>\n",
       "      <td>0.021121</td>\n",
       "      <td>-0.018570</td>\n",
       "      <td>-0.001558</td>\n",
       "      <td>0.000083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gender</th>\n",
       "      <td>-0.009507</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.002559</td>\n",
       "      <td>0.001405</td>\n",
       "      <td>0.016551</td>\n",
       "      <td>-0.000901</td>\n",
       "      <td>-0.009100</td>\n",
       "      <td>-0.020542</td>\n",
       "      <td>-0.001532</td>\n",
       "      <td>-0.024294</td>\n",
       "      <td>...</td>\n",
       "      <td>0.008494</td>\n",
       "      <td>-0.001671</td>\n",
       "      <td>0.002345</td>\n",
       "      <td>-0.002522</td>\n",
       "      <td>0.007070</td>\n",
       "      <td>-0.002362</td>\n",
       "      <td>0.020832</td>\n",
       "      <td>-0.016036</td>\n",
       "      <td>-0.001008</td>\n",
       "      <td>-0.004329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <td>0.005225</td>\n",
       "      <td>-0.002559</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.030336</td>\n",
       "      <td>-0.203950</td>\n",
       "      <td>0.026823</td>\n",
       "      <td>0.002462</td>\n",
       "      <td>0.148820</td>\n",
       "      <td>-0.043003</td>\n",
       "      <td>-0.131719</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.007365</td>\n",
       "      <td>-0.150035</td>\n",
       "      <td>0.041384</td>\n",
       "      <td>0.063616</td>\n",
       "      <td>-0.139937</td>\n",
       "      <td>0.153214</td>\n",
       "      <td>-0.042480</td>\n",
       "      <td>0.227606</td>\n",
       "      <td>0.114288</td>\n",
       "      <td>0.151732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Partner</th>\n",
       "      <td>-0.002615</td>\n",
       "      <td>0.001405</td>\n",
       "      <td>0.030336</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.450194</td>\n",
       "      <td>0.379378</td>\n",
       "      <td>0.020985</td>\n",
       "      <td>0.141687</td>\n",
       "      <td>0.010114</td>\n",
       "      <td>0.152532</td>\n",
       "      <td>...</td>\n",
       "      <td>0.167621</td>\n",
       "      <td>0.120429</td>\n",
       "      <td>0.124379</td>\n",
       "      <td>0.130106</td>\n",
       "      <td>0.289554</td>\n",
       "      <td>-0.027336</td>\n",
       "      <td>-0.155145</td>\n",
       "      <td>0.092356</td>\n",
       "      <td>0.315334</td>\n",
       "      <td>-0.151653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dependents</th>\n",
       "      <td>0.001807</td>\n",
       "      <td>0.016551</td>\n",
       "      <td>-0.203950</td>\n",
       "      <td>0.450194</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.160499</td>\n",
       "      <td>0.002272</td>\n",
       "      <td>-0.027696</td>\n",
       "      <td>0.042555</td>\n",
       "      <td>0.161968</td>\n",
       "      <td>...</td>\n",
       "      <td>0.087291</td>\n",
       "      <td>0.135168</td>\n",
       "      <td>0.038292</td>\n",
       "      <td>0.020792</td>\n",
       "      <td>0.244473</td>\n",
       "      <td>-0.105486</td>\n",
       "      <td>-0.036673</td>\n",
       "      <td>-0.112758</td>\n",
       "      <td>0.067310</td>\n",
       "      <td>-0.171648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tenure</th>\n",
       "      <td>0.008353</td>\n",
       "      <td>-0.000901</td>\n",
       "      <td>0.026823</td>\n",
       "      <td>0.379378</td>\n",
       "      <td>0.160499</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.012829</td>\n",
       "      <td>0.342546</td>\n",
       "      <td>-0.014933</td>\n",
       "      <td>0.321572</td>\n",
       "      <td>...</td>\n",
       "      <td>0.370768</td>\n",
       "      <td>0.319787</td>\n",
       "      <td>0.290031</td>\n",
       "      <td>0.298498</td>\n",
       "      <td>0.671260</td>\n",
       "      <td>0.001573</td>\n",
       "      <td>-0.377989</td>\n",
       "      <td>0.244162</td>\n",
       "      <td>0.822968</td>\n",
       "      <td>-0.351598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PhoneService</th>\n",
       "      <td>-0.027008</td>\n",
       "      <td>-0.009100</td>\n",
       "      <td>0.002462</td>\n",
       "      <td>0.020985</td>\n",
       "      <td>0.002272</td>\n",
       "      <td>0.012829</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.021138</td>\n",
       "      <td>0.390248</td>\n",
       "      <td>-0.010066</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.002147</td>\n",
       "      <td>-0.011736</td>\n",
       "      <td>0.047852</td>\n",
       "      <td>0.053231</td>\n",
       "      <td>0.006604</td>\n",
       "      <td>0.012392</td>\n",
       "      <td>-0.009900</td>\n",
       "      <td>0.247079</td>\n",
       "      <td>0.114592</td>\n",
       "      <td>0.012515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MultipleLines</th>\n",
       "      <td>-0.005665</td>\n",
       "      <td>-0.020542</td>\n",
       "      <td>0.148820</td>\n",
       "      <td>0.141687</td>\n",
       "      <td>-0.027696</td>\n",
       "      <td>0.342546</td>\n",
       "      <td>-0.021138</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.106991</td>\n",
       "      <td>0.006508</td>\n",
       "      <td>...</td>\n",
       "      <td>0.108733</td>\n",
       "      <td>0.002981</td>\n",
       "      <td>0.173073</td>\n",
       "      <td>0.180521</td>\n",
       "      <td>0.110553</td>\n",
       "      <td>0.164679</td>\n",
       "      <td>-0.177618</td>\n",
       "      <td>0.436287</td>\n",
       "      <td>0.453762</td>\n",
       "      <td>0.044104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>InternetService</th>\n",
       "      <td>-0.001766</td>\n",
       "      <td>-0.001532</td>\n",
       "      <td>-0.043003</td>\n",
       "      <td>0.010114</td>\n",
       "      <td>0.042555</td>\n",
       "      <td>-0.014933</td>\n",
       "      <td>0.390248</td>\n",
       "      <td>-0.106991</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.013036</td>\n",
       "      <td>...</td>\n",
       "      <td>0.048778</td>\n",
       "      <td>-0.014065</td>\n",
       "      <td>0.102128</td>\n",
       "      <td>0.108239</td>\n",
       "      <td>0.108912</td>\n",
       "      <td>-0.136533</td>\n",
       "      <td>0.079433</td>\n",
       "      <td>-0.320720</td>\n",
       "      <td>-0.166218</td>\n",
       "      <td>-0.049542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <td>0.007574</td>\n",
       "      <td>-0.024294</td>\n",
       "      <td>-0.131719</td>\n",
       "      <td>0.152532</td>\n",
       "      <td>0.161968</td>\n",
       "      <td>0.321572</td>\n",
       "      <td>-0.010066</td>\n",
       "      <td>0.006508</td>\n",
       "      <td>-0.013036</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.171345</td>\n",
       "      <td>0.292574</td>\n",
       "      <td>0.053197</td>\n",
       "      <td>0.058040</td>\n",
       "      <td>0.376497</td>\n",
       "      <td>-0.168525</td>\n",
       "      <td>-0.101626</td>\n",
       "      <td>-0.060525</td>\n",
       "      <td>0.248385</td>\n",
       "      <td>-0.287888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OnlineBackup</th>\n",
       "      <td>0.002747</td>\n",
       "      <td>-0.013820</td>\n",
       "      <td>-0.008885</td>\n",
       "      <td>0.156795</td>\n",
       "      <td>0.093931</td>\n",
       "      <td>0.383118</td>\n",
       "      <td>0.011534</td>\n",
       "      <td>0.125779</td>\n",
       "      <td>0.043034</td>\n",
       "      <td>0.185291</td>\n",
       "      <td>...</td>\n",
       "      <td>0.203988</td>\n",
       "      <td>0.196340</td>\n",
       "      <td>0.156057</td>\n",
       "      <td>0.153739</td>\n",
       "      <td>0.287789</td>\n",
       "      <td>-0.006362</td>\n",
       "      <td>-0.131993</td>\n",
       "      <td>0.126095</td>\n",
       "      <td>0.388330</td>\n",
       "      <td>-0.192078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DeviceProtection</th>\n",
       "      <td>-0.002294</td>\n",
       "      <td>0.008494</td>\n",
       "      <td>-0.007365</td>\n",
       "      <td>0.167621</td>\n",
       "      <td>0.087291</td>\n",
       "      <td>0.370768</td>\n",
       "      <td>-0.002147</td>\n",
       "      <td>0.108733</td>\n",
       "      <td>0.048778</td>\n",
       "      <td>0.171345</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.234423</td>\n",
       "      <td>0.275339</td>\n",
       "      <td>0.294975</td>\n",
       "      <td>0.343693</td>\n",
       "      <td>-0.033953</td>\n",
       "      <td>-0.149058</td>\n",
       "      <td>0.159285</td>\n",
       "      <td>0.384920</td>\n",
       "      <td>-0.173445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TechSupport</th>\n",
       "      <td>0.002778</td>\n",
       "      <td>-0.001671</td>\n",
       "      <td>-0.150035</td>\n",
       "      <td>0.120429</td>\n",
       "      <td>0.135168</td>\n",
       "      <td>0.319787</td>\n",
       "      <td>-0.011736</td>\n",
       "      <td>0.002981</td>\n",
       "      <td>-0.014065</td>\n",
       "      <td>0.292574</td>\n",
       "      <td>...</td>\n",
       "      <td>0.234423</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.154619</td>\n",
       "      <td>0.152804</td>\n",
       "      <td>0.423046</td>\n",
       "      <td>-0.110451</td>\n",
       "      <td>-0.097724</td>\n",
       "      <td>-0.012453</td>\n",
       "      <td>0.269871</td>\n",
       "      <td>-0.285600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StreamingTV</th>\n",
       "      <td>-0.005301</td>\n",
       "      <td>0.002345</td>\n",
       "      <td>0.041384</td>\n",
       "      <td>0.124379</td>\n",
       "      <td>0.038292</td>\n",
       "      <td>0.290031</td>\n",
       "      <td>0.047852</td>\n",
       "      <td>0.173073</td>\n",
       "      <td>0.102128</td>\n",
       "      <td>0.053197</td>\n",
       "      <td>...</td>\n",
       "      <td>0.275339</td>\n",
       "      <td>0.154619</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.432680</td>\n",
       "      <td>0.224886</td>\n",
       "      <td>0.099546</td>\n",
       "      <td>-0.107879</td>\n",
       "      <td>0.334519</td>\n",
       "      <td>0.389178</td>\n",
       "      <td>-0.037225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StreamingMovies</th>\n",
       "      <td>-0.022339</td>\n",
       "      <td>-0.002522</td>\n",
       "      <td>0.063616</td>\n",
       "      <td>0.130106</td>\n",
       "      <td>0.020792</td>\n",
       "      <td>0.298498</td>\n",
       "      <td>0.053231</td>\n",
       "      <td>0.180521</td>\n",
       "      <td>0.108239</td>\n",
       "      <td>0.058040</td>\n",
       "      <td>...</td>\n",
       "      <td>0.294975</td>\n",
       "      <td>0.152804</td>\n",
       "      <td>0.432680</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.234617</td>\n",
       "      <td>0.079168</td>\n",
       "      <td>-0.125042</td>\n",
       "      <td>0.344324</td>\n",
       "      <td>0.402530</td>\n",
       "      <td>-0.038751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Contract</th>\n",
       "      <td>0.005255</td>\n",
       "      <td>0.007070</td>\n",
       "      <td>-0.139937</td>\n",
       "      <td>0.289554</td>\n",
       "      <td>0.244473</td>\n",
       "      <td>0.671260</td>\n",
       "      <td>0.006604</td>\n",
       "      <td>0.110553</td>\n",
       "      <td>0.108912</td>\n",
       "      <td>0.376497</td>\n",
       "      <td>...</td>\n",
       "      <td>0.343693</td>\n",
       "      <td>0.423046</td>\n",
       "      <td>0.224886</td>\n",
       "      <td>0.234617</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.177763</td>\n",
       "      <td>-0.232491</td>\n",
       "      <td>-0.076027</td>\n",
       "      <td>0.447411</td>\n",
       "      <td>-0.400353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <td>0.000142</td>\n",
       "      <td>-0.002362</td>\n",
       "      <td>0.153214</td>\n",
       "      <td>-0.027336</td>\n",
       "      <td>-0.105486</td>\n",
       "      <td>0.001573</td>\n",
       "      <td>0.012392</td>\n",
       "      <td>0.164679</td>\n",
       "      <td>-0.136533</td>\n",
       "      <td>-0.168525</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.033953</td>\n",
       "      <td>-0.110451</td>\n",
       "      <td>0.099546</td>\n",
       "      <td>0.079168</td>\n",
       "      <td>-0.177763</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.067396</td>\n",
       "      <td>0.349757</td>\n",
       "      <td>0.153736</td>\n",
       "      <td>0.196975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PaymentMethod</th>\n",
       "      <td>0.021121</td>\n",
       "      <td>0.020832</td>\n",
       "      <td>-0.042480</td>\n",
       "      <td>-0.155145</td>\n",
       "      <td>-0.036673</td>\n",
       "      <td>-0.377989</td>\n",
       "      <td>-0.009900</td>\n",
       "      <td>-0.177618</td>\n",
       "      <td>0.079433</td>\n",
       "      <td>-0.101626</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.149058</td>\n",
       "      <td>-0.097724</td>\n",
       "      <td>-0.107879</td>\n",
       "      <td>-0.125042</td>\n",
       "      <td>-0.232491</td>\n",
       "      <td>-0.067396</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.199981</td>\n",
       "      <td>-0.338072</td>\n",
       "      <td>0.116393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <td>-0.018570</td>\n",
       "      <td>-0.016036</td>\n",
       "      <td>0.227606</td>\n",
       "      <td>0.092356</td>\n",
       "      <td>-0.112758</td>\n",
       "      <td>0.244162</td>\n",
       "      <td>0.247079</td>\n",
       "      <td>0.436287</td>\n",
       "      <td>-0.320720</td>\n",
       "      <td>-0.060525</td>\n",
       "      <td>...</td>\n",
       "      <td>0.159285</td>\n",
       "      <td>-0.012453</td>\n",
       "      <td>0.334519</td>\n",
       "      <td>0.344324</td>\n",
       "      <td>-0.076027</td>\n",
       "      <td>0.349757</td>\n",
       "      <td>-0.199981</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.649092</td>\n",
       "      <td>0.195558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalCharges</th>\n",
       "      <td>-0.001558</td>\n",
       "      <td>-0.001008</td>\n",
       "      <td>0.114288</td>\n",
       "      <td>0.315334</td>\n",
       "      <td>0.067310</td>\n",
       "      <td>0.822968</td>\n",
       "      <td>0.114592</td>\n",
       "      <td>0.453762</td>\n",
       "      <td>-0.166218</td>\n",
       "      <td>0.248385</td>\n",
       "      <td>...</td>\n",
       "      <td>0.384920</td>\n",
       "      <td>0.269871</td>\n",
       "      <td>0.389178</td>\n",
       "      <td>0.402530</td>\n",
       "      <td>0.447411</td>\n",
       "      <td>0.153736</td>\n",
       "      <td>-0.338072</td>\n",
       "      <td>0.649092</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.197197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Churn</th>\n",
       "      <td>0.000083</td>\n",
       "      <td>-0.004329</td>\n",
       "      <td>0.151732</td>\n",
       "      <td>-0.151653</td>\n",
       "      <td>-0.171648</td>\n",
       "      <td>-0.351598</td>\n",
       "      <td>0.012515</td>\n",
       "      <td>0.044104</td>\n",
       "      <td>-0.049542</td>\n",
       "      <td>-0.287888</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.173445</td>\n",
       "      <td>-0.285600</td>\n",
       "      <td>-0.037225</td>\n",
       "      <td>-0.038751</td>\n",
       "      <td>-0.400353</td>\n",
       "      <td>0.196975</td>\n",
       "      <td>0.116393</td>\n",
       "      <td>0.195558</td>\n",
       "      <td>-0.197197</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Id    gender  SeniorCitizen   Partner  Dependents  \\\n",
       "Id                1.000000 -0.009507       0.005225 -0.002615    0.001807   \n",
       "gender           -0.009507  1.000000      -0.002559  0.001405    0.016551   \n",
       "SeniorCitizen     0.005225 -0.002559       1.000000  0.030336   -0.203950   \n",
       "Partner          -0.002615  0.001405       0.030336  1.000000    0.450194   \n",
       "Dependents        0.001807  0.016551      -0.203950  0.450194    1.000000   \n",
       "tenure            0.008353 -0.000901       0.026823  0.379378    0.160499   \n",
       "PhoneService     -0.027008 -0.009100       0.002462  0.020985    0.002272   \n",
       "MultipleLines    -0.005665 -0.020542       0.148820  0.141687   -0.027696   \n",
       "InternetService  -0.001766 -0.001532      -0.043003  0.010114    0.042555   \n",
       "OnlineSecurity    0.007574 -0.024294      -0.131719  0.152532    0.161968   \n",
       "OnlineBackup      0.002747 -0.013820      -0.008885  0.156795    0.093931   \n",
       "DeviceProtection -0.002294  0.008494      -0.007365  0.167621    0.087291   \n",
       "TechSupport       0.002778 -0.001671      -0.150035  0.120429    0.135168   \n",
       "StreamingTV      -0.005301  0.002345       0.041384  0.124379    0.038292   \n",
       "StreamingMovies  -0.022339 -0.002522       0.063616  0.130106    0.020792   \n",
       "Contract          0.005255  0.007070      -0.139937  0.289554    0.244473   \n",
       "PaperlessBilling  0.000142 -0.002362       0.153214 -0.027336   -0.105486   \n",
       "PaymentMethod     0.021121  0.020832      -0.042480 -0.155145   -0.036673   \n",
       "MonthlyCharges   -0.018570 -0.016036       0.227606  0.092356   -0.112758   \n",
       "TotalCharges     -0.001558 -0.001008       0.114288  0.315334    0.067310   \n",
       "Churn             0.000083 -0.004329       0.151732 -0.151653   -0.171648   \n",
       "\n",
       "                    tenure  PhoneService  MultipleLines  InternetService  \\\n",
       "Id                0.008353     -0.027008      -0.005665        -0.001766   \n",
       "gender           -0.000901     -0.009100      -0.020542        -0.001532   \n",
       "SeniorCitizen     0.026823      0.002462       0.148820        -0.043003   \n",
       "Partner           0.379378      0.020985       0.141687         0.010114   \n",
       "Dependents        0.160499      0.002272      -0.027696         0.042555   \n",
       "tenure            1.000000      0.012829       0.342546        -0.014933   \n",
       "PhoneService      0.012829      1.000000      -0.021138         0.390248   \n",
       "MultipleLines     0.342546     -0.021138       1.000000        -0.106991   \n",
       "InternetService  -0.014933      0.390248      -0.106991         1.000000   \n",
       "OnlineSecurity    0.321572     -0.010066       0.006508        -0.013036   \n",
       "OnlineBackup      0.383118      0.011534       0.125779         0.043034   \n",
       "DeviceProtection  0.370768     -0.002147       0.108733         0.048778   \n",
       "TechSupport       0.319787     -0.011736       0.002981        -0.014065   \n",
       "StreamingTV       0.290031      0.047852       0.173073         0.102128   \n",
       "StreamingMovies   0.298498      0.053231       0.180521         0.108239   \n",
       "Contract          0.671260      0.006604       0.110553         0.108912   \n",
       "PaperlessBilling  0.001573      0.012392       0.164679        -0.136533   \n",
       "PaymentMethod    -0.377989     -0.009900      -0.177618         0.079433   \n",
       "MonthlyCharges    0.244162      0.247079       0.436287        -0.320720   \n",
       "TotalCharges      0.822968      0.114592       0.453762        -0.166218   \n",
       "Churn            -0.351598      0.012515       0.044104        -0.049542   \n",
       "\n",
       "                  OnlineSecurity  ...  DeviceProtection  TechSupport  \\\n",
       "Id                      0.007574  ...         -0.002294     0.002778   \n",
       "gender                 -0.024294  ...          0.008494    -0.001671   \n",
       "SeniorCitizen          -0.131719  ...         -0.007365    -0.150035   \n",
       "Partner                 0.152532  ...          0.167621     0.120429   \n",
       "Dependents              0.161968  ...          0.087291     0.135168   \n",
       "tenure                  0.321572  ...          0.370768     0.319787   \n",
       "PhoneService           -0.010066  ...         -0.002147    -0.011736   \n",
       "MultipleLines           0.006508  ...          0.108733     0.002981   \n",
       "InternetService        -0.013036  ...          0.048778    -0.014065   \n",
       "OnlineSecurity          1.000000  ...          0.171345     0.292574   \n",
       "OnlineBackup            0.185291  ...          0.203988     0.196340   \n",
       "DeviceProtection        0.171345  ...          1.000000     0.234423   \n",
       "TechSupport             0.292574  ...          0.234423     1.000000   \n",
       "StreamingTV             0.053197  ...          0.275339     0.154619   \n",
       "StreamingMovies         0.058040  ...          0.294975     0.152804   \n",
       "Contract                0.376497  ...          0.343693     0.423046   \n",
       "PaperlessBilling       -0.168525  ...         -0.033953    -0.110451   \n",
       "PaymentMethod          -0.101626  ...         -0.149058    -0.097724   \n",
       "MonthlyCharges         -0.060525  ...          0.159285    -0.012453   \n",
       "TotalCharges            0.248385  ...          0.384920     0.269871   \n",
       "Churn                  -0.287888  ...         -0.173445    -0.285600   \n",
       "\n",
       "                  StreamingTV  StreamingMovies  Contract  PaperlessBilling  \\\n",
       "Id                  -0.005301        -0.022339  0.005255          0.000142   \n",
       "gender               0.002345        -0.002522  0.007070         -0.002362   \n",
       "SeniorCitizen        0.041384         0.063616 -0.139937          0.153214   \n",
       "Partner              0.124379         0.130106  0.289554         -0.027336   \n",
       "Dependents           0.038292         0.020792  0.244473         -0.105486   \n",
       "tenure               0.290031         0.298498  0.671260          0.001573   \n",
       "PhoneService         0.047852         0.053231  0.006604          0.012392   \n",
       "MultipleLines        0.173073         0.180521  0.110553          0.164679   \n",
       "InternetService      0.102128         0.108239  0.108912         -0.136533   \n",
       "OnlineSecurity       0.053197         0.058040  0.376497         -0.168525   \n",
       "OnlineBackup         0.156057         0.153739  0.287789         -0.006362   \n",
       "DeviceProtection     0.275339         0.294975  0.343693         -0.033953   \n",
       "TechSupport          0.154619         0.152804  0.423046         -0.110451   \n",
       "StreamingTV          1.000000         0.432680  0.224886          0.099546   \n",
       "StreamingMovies      0.432680         1.000000  0.234617          0.079168   \n",
       "Contract             0.224886         0.234617  1.000000         -0.177763   \n",
       "PaperlessBilling     0.099546         0.079168 -0.177763          1.000000   \n",
       "PaymentMethod       -0.107879        -0.125042 -0.232491         -0.067396   \n",
       "MonthlyCharges       0.334519         0.344324 -0.076027          0.349757   \n",
       "TotalCharges         0.389178         0.402530  0.447411          0.153736   \n",
       "Churn               -0.037225        -0.038751 -0.400353          0.196975   \n",
       "\n",
       "                  PaymentMethod  MonthlyCharges  TotalCharges     Churn  \n",
       "Id                     0.021121       -0.018570     -0.001558  0.000083  \n",
       "gender                 0.020832       -0.016036     -0.001008 -0.004329  \n",
       "SeniorCitizen         -0.042480        0.227606      0.114288  0.151732  \n",
       "Partner               -0.155145        0.092356      0.315334 -0.151653  \n",
       "Dependents            -0.036673       -0.112758      0.067310 -0.171648  \n",
       "tenure                -0.377989        0.244162      0.822968 -0.351598  \n",
       "PhoneService          -0.009900        0.247079      0.114592  0.012515  \n",
       "MultipleLines         -0.177618        0.436287      0.453762  0.044104  \n",
       "InternetService        0.079433       -0.320720     -0.166218 -0.049542  \n",
       "OnlineSecurity        -0.101626       -0.060525      0.248385 -0.287888  \n",
       "OnlineBackup          -0.131993        0.126095      0.388330 -0.192078  \n",
       "DeviceProtection      -0.149058        0.159285      0.384920 -0.173445  \n",
       "TechSupport           -0.097724       -0.012453      0.269871 -0.285600  \n",
       "StreamingTV           -0.107879        0.334519      0.389178 -0.037225  \n",
       "StreamingMovies       -0.125042        0.344324      0.402530 -0.038751  \n",
       "Contract              -0.232491       -0.076027      0.447411 -0.400353  \n",
       "PaperlessBilling      -0.067396        0.349757      0.153736  0.196975  \n",
       "PaymentMethod          1.000000       -0.199981     -0.338072  0.116393  \n",
       "MonthlyCharges        -0.199981        1.000000      0.649092  0.195558  \n",
       "TotalCharges          -0.338072        0.649092      1.000000 -0.197197  \n",
       "Churn                  0.116393        0.195558     -0.197197  1.000000  \n",
       "\n",
       "[21 rows x 21 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model building"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sclae the data\n",
    "X = train.drop('Churn', axis = 1)\n",
    "y = train['Churn']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = StandardScaler().fit_transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.3, random_state = 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7959787108219988\n"
     ]
    }
   ],
   "source": [
    "# Fit Model\n",
    "model = LogisticRegression()\n",
    "model.fit(X_train, y_train)\n",
    "predict = model.predict(X_test)\n",
    "print(accuracy_score(y_test, predict))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Score of AdaBoost :  0.7900650502661147\n",
      "Confusion matrix: \n",
      " [[1086  158]\n",
      " [ 197  250]]\n",
      "Classification report: \n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       0.85      0.87      0.86      1244\n",
      "           1       0.61      0.56      0.58       447\n",
      "\n",
      "    accuracy                           0.79      1691\n",
      "   macro avg       0.73      0.72      0.72      1691\n",
      "weighted avg       0.78      0.79      0.79      1691\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Fitting AdaBoost\n",
    "ada_clf = AdaBoostClassifier(random_state =3)\n",
    "ada_clf.fit(X_train, y_train)\n",
    "y_pred_ada = ada_clf.predict(X_test)\n",
    "ada_score = accuracy_score(y_test, y_pred_ada)\n",
    "print('Score of AdaBoost : ', ada_score)\n",
    "\n",
    "#Finding the confusion matrix\n",
    "ada_cm=confusion_matrix(y_test,y_pred_ada)\n",
    "print('Confusion matrix: \\n', ada_cm)\n",
    "\n",
    "#Finding the classification report\n",
    "ada_cr=classification_report(y_test,y_pred_ada)\n",
    "print('Classification report: \\n', ada_cr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Score of XG Boost : 0.7717327025428741\n",
      "Confusion matrix: \n",
      " [[1081  163]\n",
      " [ 223  224]]\n",
      "Classification report: \n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       0.83      0.87      0.85      1244\n",
      "           1       0.58      0.50      0.54       447\n",
      "\n",
      "    accuracy                           0.77      1691\n",
      "   macro avg       0.70      0.69      0.69      1691\n",
      "weighted avg       0.76      0.77      0.77      1691\n",
      "\n"
     ]
    }
   ],
   "source": [
    "xgb_clf = XGBClassifier(random_state = 3)\n",
    "xgb_clf.fit(X_train, y_train)\n",
    "y_pred_xgb = xgb_clf.predict(X_test)\n",
    "xgb_score = accuracy_score(y_test, y_pred_xgb)\n",
    "print('Score of XG Boost :',xgb_score)\n",
    "\n",
    "#Finding the confusion matrix\n",
    "xgb_cm=confusion_matrix(y_test,y_pred_xgb)\n",
    "print('Confusion matrix: \\n', xgb_cm)\n",
    "\n",
    "#Finding the classification report\n",
    "xgb_cr=classification_report(y_test,y_pred_xgb)\n",
    "print('Classification report: \\n', xgb_cr)"
   ]
  }
 ],
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